CNTK is also one of the first deep-learning toolkits to support the Open Neural Network Exchange ONNX format, an open-source shared model representation for framework interoperability and shared optimization.

Among the various fields of exploration in artificial intelligence, deep learning is an exciting and increasingly important area of research that holds great potential for helping computers understand and extract meaning from data, e.g.

The ONNX initiative envisions the flexibility to move deep learning models seamlessly between open-source frameworks to accelerate development for data scientists.

If you prefer to use latest CNTK bits from master, use one of the CNTK nightly packages: You can learn more about using and contributing to CNTK with the following resources: CNTK is in active use at Microsoft and constantly evolving.

Please check out the example of FP16 in ResNet50 here Notes on FP16 preview: To setup build and runtime environment on Windows: To setup build and runtime environment on Linux using docker, please build Unbuntu 16.04 docker image using Dockerfiles here.

CNTK is also one of the first deep-learning toolkits to support the Open Neural Network Exchange ONNX format, an open-source shared model representation for framework interoperability and shared optimization.

On Monday, January 21, 2019

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